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Stochastic and Statistical Methods in Hydrology and Environmental Engineering pp 397–409Cite as

Incorporating Uncertainty in Energy Demand in a Reservoir Reliability Planning Model

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Part of the book series: Water Science and Technology Library ((WSTL,volume 10/2))

Abstract

A ‘basic’ reliability model for planning the operation of a multipurpose reservoir for hydropower generation and flood control has been developed by the authors in their earlier research. This model considers the reservoir inflows as stochastic and the energy demands and cost coefficients as deterministic. The proposed solution algorithm maximizes the benefits accrued from hydropower generation and minimizes the economic losses incurred due to the reservoir not meeting the required reliabilities for hydroenergy supply and flood control. The model determines the optimal reservoir release policy along with the optimal values of the reliabilities for these two purposes.

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Author information

Authors and Affiliations

  1. Dept. of Civil and Geological Engineering, University of Manitoba, Winnipeg, Canada, R3T 5V6

    R. Srinivasan & S. P. Simonovic

Authors
  1. R. Srinivasan
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  2. S. P. Simonovic
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Editor information

Editors and Affiliations

  1. Departments of Systems Design Engineering and Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada

    Keith W. Hipel (Professor and Chair) & Liping Fang (Assistant Professor) (Professor and Chair) &  (Assistant Professor)

  2. Department of Mechanical Engineering, Ryerson Polytechnic University, Toronto, Ontario, Canada

    Liping Fang (Assistant Professor) (Assistant Professor)

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© 1994 Springer Science+Business Media Dordrecht

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Srinivasan, R., Simonovic, S.P. (1994). Incorporating Uncertainty in Energy Demand in a Reservoir Reliability Planning Model. In: Hipel, K.W., Fang, L. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/2. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3081-5_30

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  • DOI: https://doi.org/10.1007/978-94-017-3081-5_30

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4380-1

  • Online ISBN: 978-94-017-3081-5

  • eBook Packages: Springer Book Archive

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